Cross-Sell Opportunity Formulation for a reputed bank

Client: A new bank moving to target its liability customers for asset products

Building a Decision Tree Model to help identify customers susceptible to cross change initiatives

Case Study

Summary

• Our client was trying to find out ways to gain wallet-share of it customers (savings & current a/c holder)

• It was looking for a Decision Tree model to give likely list of leads so as to focus the marketing campaigns towards them.

• Our client was trying to find out ways to gain wallet-share of it customers (savings & current a/c holder)

• It was looking for a Decision Tree model to give likely list of leads so as to focus the marketing campaigns towards them.

Business Objective

• Cequity identified the variables which makes the difference through rigorous statistical modeling and analysis

• Once the variables were identified , the best possible path to reach high propensity customers through decision tree modeling

• Cequity identified the variables which makes the difference through rigorous statistical modeling and analysis

• Once the variables were identified , the best possible path to reach high propensity customers through decision tree modeling

Solution

• We built a quantifiable model for client to reach the best leads through decile treatment

• Based on the behavior pattern, we could predict the right offerings for each segments.

• There was a huge lift in conversion rate for our client using the Cequity model. Marketing & campaigning spends were also optimized.

• We built a quantifiable model for client to reach the best leads through decile treatment

• Based on the behavior pattern, we could predict the right offerings for each segments.

• There was a huge lift in conversion rate for our client using the Cequity model. Marketing & campaigning spends were also optimized.

Results

Business Objective

Our client was facing low conversion rate in cross-selling the Assets products to its Liability customers. Although the Liability and Asset products have been on the market for quite some years, the overlaps for its customer into these Venns were very low.

But it would have been imprudent to expend marketing resources on entire liability customer base with for cross-selling them asset product. It was desperately looking for a model to focus its resources better.

We built a Cross-Sell model taking into consideration all factors like Demographics, Transactions, Psychographics and Response from previous campaigns.

The result was evolution of a non-linear model for predicting the chances of buying its asset products within its liability customer base.

Solution – Finding out micro segments

Uni-Variate Analysis Multi-Variate Analysis

Criteria

Marital Status =

XXX

Ledger balance < XXX

Number of Fixed

deposits < X

Amountcredited in

last x months > xxx

Response Rate

Y1%

Y2%

Y3%

Y4%

Criteria

Marital Status = XXX

Marital Status = XXX & Ledger balance

< XXX

Marital Status = XXX & Ledger balance < XXX

&Number of Fixed deposits < X

Marital Status = XXX & Ledger balance < XXX & Number of Fixed

deposits < X & Amountcredited in last x

months > xxx

Response Rate

X1%

X2%

X3%

X4%

Quantum leap in targeting

the right customers

Solution – Analysis

Criteria

Marital Status =

XXX

Ledger balance < XXX

Number of Fixed

deposits < X

Amountcredited in

last x months > xxx

Response Rate

Y1%

Y2%

Y3%

Y4%

Criteria

Marital Status = XXX

Marital Status = XXX & Ledger balance

< XXX

Marital Status = XXX & Ledger balance < XXX

&Number of Fixed deposits < X

Marital Status = XXX & Ledger balance < XXX & Number of Fixed

deposits < X & Amountcredited in last x

months > xxx

Response Rate

X1%

X2%

X3%

X4%

Empower with The Power of Multi-VariateAnalysis

X4 is much much higher

than Y4

Uni-Variate Analysis Multi-Variate Analysis

6

Gain 49%

Gain 45%

Gain 39%

Gain 35%

Gain 28%

Gain 18%

Incre

asin

g G

ain

–“G

oo

d”

cu

sto

mer

ch

ara

cte

rist

icsCriterion # 1

Supervised Classification on 6,00,000

Criterion # 3(MOB)

< x months x – y months y-z months z+ months

Criterion # 5 (occupation)

Self employed Employed with PSU

Employed with Corporate setup

Small scale business person

Criterion # 2 (montly avg

balance)

< INR xxx INR xxx – xxx INR xxx – INR xxx > INR xxxINR xxx – INR xxx

Criterion # 4 (# of debits)

0-a debits a-b debits c-d debits d+ debitsb-c debits

Criterion # 6 (age group)

p-q yrs q-r yrs r-s yrs > s yrs

Gain X1

%

Gain X2

%

Gain X3

%

Gain X4

%

Gain X5

%

Gain X6

%

Solution – Building the Decision Tree

7

Gain 49%

Gain 45%

Gain 39%

Gain 35%

Gain 28%

Gain 18%

The customers belonging to the adjacent segment would be the preferred target for our cross sell exercise (a given asset product)

Monthly Avg Bal INR XXXMonths on books x-y months# of debits b-c debitsOccupation XXXAge group q - ryrs

Incre

asin

g G

ain

–“G

oo

d”

cu

sto

mer

ch

ara

cte

rist

icsCriterion # 1

Supervised Classification on 6,00,000

Criterion # 3(MOB)

< x months x – y months y-z months z+ months

Criterion # 5 (occupation)

Self employed Employed with PSU

Employed with Corporate setup

Small scale business person

Criterion # 2 (montly avg

balance)

< INR xxx INR xxx – xxx INR xxx – INR xxx > INR xxxINR xxx – INR xxx

Criterion # 4 (# of debits)

0-a debits a-b debits c-d debits d+ debitsb-c debits

Criterion # 6 (age group)

p-q yrs q-r yrs r-s yrs > s yrs

Gain X1

%

Gain X2

%

Gain X3

%

Gain X4

%

Gain X5

%

Gain X6

%

The Ideal Profile

Solution – Building the Decision Tree

Results

Target right customer with right product

Identify customers in Top Deciles who have propensity of buying an Asset product

Increased Response rates and conversions

Optimized marketing efforts and spend

Thank you

Customer Equity Solutions Pvt. Ltd.

Worldwide Offices

INDIA USA Mumbai Office: 105-106, 1st Floor, Chicago Office: 626, Anand Estate, 189-A, Grove Street, Evantson, IL Sane Guruji Marg, Mahalaxmi, 60201 Mumbai-400 011Phone: +91 22 4345 3800 Fax: +91 22 4345 3840

www.CequitySolutions.com

Customer Equity Solutions Pvt. Ltd.

Worldwide Offices

INDIA USA Mumbai Office: 105-106, 1st Floor, Chicago Office: 626, Anand Estate, 189-A, Grove Street, Evantson, IL Sane Guruji Marg, Mahalaxmi, 60201 Mumbai-400 011Phone: +91 22 4345 3800 Fax: +91 22 4345 3840

www.CequitySolutions.com